Multi-Mode Tensor Representation of Motion Data

In this paper, we investigate how a multilinear model can be used to represent human motion data. Based on technical modes (referring to degrees of freedom and number of frames) and natural modes that typically appear in the context of a motion capture session (referring to actor, style, and repetition), the motion data is encoded in form of a high-order tensor. This tensor is then reduced by using N-mode singular value decomposition. Our experiments show that the reduced model approximates the original motion better then previously introduced PCA-based approaches. Furthermore, we discuss how the tensor representation may be used as a valuable tool for the synthesis of new motions.

Who has really paid for the Reconstruction of East Germany? Expected and Realized Returns on Real Estate Investments in East and West Germany in the 1990s

We evaluate the profitability of investments in residential property in Germany after unification with a focus on the comparison of East and West Germany. Calculations are carried out for (1) the after-tax return an investor might have expected at the beginning of the 1990s, and (2) the after-tax return that has been realized ten years after. We compare a set of statistical data for investments in fifty major cities by using complete financial budgeting. The results show that tax subsidies could not always protect investors from losing money, but they have boosted realized returns after tax considerably. Therefore, it was indeed the taxpayers, not the investors, who have borne the cost of reconstructing East Germany.